books

ratings

plz need big help on this one and also need those extra credits. thanks

y [US] https://cis.temple.edu/-jfiore/2018/fal/106a/assignments/07) ourse Hero I wel.- Abhishek Upmany DAVA class Assignment Description This assignment will provide you with practice using arrays. Canv crete Mathema- unty Shepherd Free Tests for ree.. Your job is to build a simple recommender system, similar to the one that Amazon uses to recommend books to customers. The basic idea is to find out some books that a user likes, and then recommend other books that the user might also like. Your Task Your program should behave as follows: 18 points Load the 20 book names and the book tatings from 30 people into two arrays in memory. These carn be read by your program using the seanser class. You are not required to handle rileniotraundException . 10 points Ask the user to enter a rating (between 1 and 5, or -1 if they haven't read it for each book. 18 points Create a method that determines for each of the 30 people a score, which represents how similar that person's tastes are to the taste of the user of the program. Store these similarity scores in an array of 30 doubles. The similarity scores should be between 0 and 1 each 18 points Create an array that represents recommended ratings for the user. There should be 20 numbers in this array, one for each book. The higher the number, the more strongly your program thinks the user will like the book. The number should be the average over all 30 ratings for the book that are greater than 0 (only include ratings for users who have actually rated the book). Howeves, it should be a weighted average people who are more similar to the current user should have a higher weight than people who are less similar. 16 points Display the name of the top book laccording to the recommended ratings from the previous step) that the user has not yet read Suggestions and hints Making a Recommendation The goal is to come up with a recommendation for a book that the user might like. If you and I have similar preferences, and there's a book that I haven't read that you like, chances are good that I might like it. Suppose there's another person, whose tastes k more evidence that I might like the book (but because my tastes only kind of match the other person's, it only lends a little bit of weight to the decision). ind of match mine, who also happens to like the book We now have even Imagine, now, that I don't just have information of a couple of friends upon which to base a recommendation. this assignment, we'll have information from 30 people about their preferences. We put all of that informati together to form a single score for G Search or type URL 8 y [US] https://cis.temple.edu/-jfiore/2018/fal/106a/assignments/07) ourse Hero I wel.- Abhishek Upmany DAVA class Assignment Description This assignment will provide you with practice using arrays. Canv crete Mathema- unty Shepherd Free Tests for ree.. Your job is to build a simple recommender system, similar to the one that Amazon uses to recommend books to customers. The basic idea is to find out some books that a user likes, and then recommend other books that the user might also like. Your Task Your program should behave as follows: 18 points Load the 20 book names and the book tatings from 30 people into two arrays in memory. These carn be read by your program using the seanser class. You are not required to handle rileniotraundException . 10 points Ask the user to enter a rating (between 1 and 5, or -1 if they haven't read it for each book. 18 points Create a method that determines for each of the 30 people a score, which represents how similar that person's tastes are to the taste of the user of the program. Store these similarity scores in an array of 30 doubles. The similarity scores should be between 0 and 1 each 18 points Create an array that represents recommended ratings for the user. There should be 20 numbers in this array, one for each book. The higher the number, the more strongly your program thinks the user will like the book. The number should be the average over all 30 ratings for the book that are greater than 0 (only include ratings for users who have actually rated the book). Howeves, it should be a weighted average people who are more similar to the current user should have a higher weight than people who are less similar. 16 points Display the name of the top book laccording to the recommended ratings from the previous step) that the user has not yet read Suggestions and hints Making a Recommendation The goal is to come up with a recommendation for a book that the user might like. If you and I have similar preferences, and there's a book that I haven't read that you like, chances are good that I might like it. Suppose there's another person, whose tastes k more evidence that I might like the book (but because my tastes only kind of match the other person's, it only lends a little bit of weight to the decision). ind of match mine, who also happens to like the book We now have even Imagine, now, that I don't just have information of a couple of friends upon which to base a recommendation. this assignment, we'll have information from 30 people about their preferences. We put all of that informati together to form a single score for G Search or type URL 8